Evaluating the Dual-Purpose of Chickpea: A Cash and Cover Crop for Agricultural Production Systems in the Southeast

Objective 1:
Year 1 (2021-22): We will evaluate 70 pre-screened Kabuli chickpea varieties and 10 commercial checks (grows in North Dakota, California, Nebraska, Washington and Montana) in mid-Nov for late March harvesting at PSREU, Citra, (North-central Florida) and NFREC, Quincy, (North Florida). The trial will be planted in a 10ft long, four-row plot in an alpha-lattice design with two replications/location with a row-to-row distance of 12 inches. Seeds will be inoculated with Cicer specific Rhizobium bacteria prior to planting to encourage nodulation. A small amount of starter N (10 pounds/acre) with a P fertilizer source will be applied for early vegetative growth. Sulfur, potassium, phosphorus and micronutrients will be applied for proper growth and yield.

We will collect following data to characterize chickpea varieties:

Emergence: We will estimate emergence after two weeks of planting by visual rating of 0-9 scale, where 0 and 9 reflects no and >90% germination, respectively.

Time to R2 & R7: We will calculate the time between planting and 50% of open flowers on the plant (R2) and 50% of pods being yellow (R7).

Cold tolerance: A 1 to 9 scale will be used following Singh et al. (1997), where 1 = no visible symptoms of damage and 9 = 100% plant killing.

Normalized difference vegetation index (NDVI): We will collect NDVI images using MicaSense Rededge camera mounted on a DJI Matrice 100 drone at 15, 30, and 45 days after emergence to assess vigor indirectly (Tucker and Sellers, 1986). Chickpeas with high NDVI will be considered as varieties that can potentially preserve moisture and suppress weeds as they have vigorous early growth.

Biomass: Fresh and dry biomass weight will be measured at 45 days after emergence to evaluate forage yield potential.

Plant height: Height will be measured after pod formation on randomly selected eight plants per replicate from the middle two rows.

Disease rating: We will rate diseases using 1 to 5 disease incidence scale (Harveson et al., 2009), where 1 = no disease and 5 = > 75% of plant showing symptoms. Disease severity will also be recorded on a 0 to 100% scale with 1% increments for each disease identified.

Pods/plants: We will count pods/plants from eight randomly selected plants in the middle two rows.
100-grain weight: We will count and weigh hundred grains after harvest.

Yield: Middle two rows will be machine harvested to estimate yield at 15% moisture.

Food qualities analysis: Total protein, digestible fiber, Fe, Zn, K and Mg in grains will be measured at UF/IFAS Forage Evaluation Support and Analytical Service Laboratory.

We will identify 6-8 varieties with best maturity, high yield potential, high food quality, disease resistance, and cold tolerance for year 2 and 3 testing.

Year 2 (2022-23): The selected 6-8 chickpea varieties and rye will be planted at PSREU and FAMU Research and Extension Center, Quincy in 4-row 20 ft long plots in a randomized complete block design with four replications/location. We will include rye in the Year 2 and 3 experiments, as rye has been the predominant growers’ preference for winter cover crop in North Florida, to evaluate the effect of chickpeas on the yield and insect infestation of corn in comparison to growers’ practice. Chickpea seeds will be inoculated before planting like Y1. All phenotypic data will be collected following the same protocols as Y1. In addition, the N-fixation capacity of chickpea varieties will be assessed (objective 2). We will conduct growers’ research assessments to select the best performing varieties for growers’ field evaluations in Y3. Following chickpea harvest, corn hybrids will be planted in mid-April in the same field for assessing N-credit (objective 2) and the effect on pests (objective 3) on the rotational crop. Corn trials will be planted in 4-row 20 ft plot with 36” row-row distance to estimate emergence, yield, test weight, etc.

Year 3 (2023-24): We will continue experiments in both PSREU and FAMU and will work with growers to conduct on-farm trials with a corn crop. The trials at PSREU and FAMU will follow the same protocol as Y2.

On farm trial: Four on-farm trials will be planted in four growers’ fields in Mariana, Monticello, Havana and Live Oak, FL to evaluate the performance of chickpea varieties (selected by growers in year 2) under growers’ field conditions. The chickpea trial will be planted in four 100 ft long strips. The trial will be assessed by growers for yield, maturity, weed suppression, fertility, etc. Following the harvesting of chickpeas, corn will be planted in the same field for the estimation of N-credit and effect on pests of corn (objectives 2 & 3).

Data will be analyzed in a linear mixed model using R package for locations, across locations, and across years and locations to estimate genotype-location interaction. The broad sense heritability for traits will be estimated. The design will be adjusted considering locations, blocks, and genotype-location interaction as random effects. PI Babar and Dr. Bolques will lead research activities and analysis for objective 1.

Objective 2:
Experimental and analytical work for objective 2 will take place during years 2 and 3 of the project, using complementary approaches for on-station research.

At PSREU, we will setup a 15N tracing experiment with the 3 most promising varieties from the 6-8 selected after year 1, selecting those most promising varieties in collaboration with the advisory council. We will label chickpea plants for these 3 varieties with 15N-enriched fertilizer, using a 30 m2 area outside of the main research plots to prevent soil contamination with 15N. We will do 4 fertilization events (foliar and soil) during chickpea growing season to obtain a uniform distribution of 15N among plant parts. We will then define a 2.5 m2 microplot for 15N experiments in each of the 12 main research plots (i.e., 3 chickpea varieties grown in 4 blocks). At chickpea termination, we will remove chickpea residues from the surface of microplots, and we will take 3 soil samples (0-15 cm) per microplot and analyze them for 15N. We will add 15N-labeled residues to the surface of microplots, at a rate identical to what the remainder of the main plots receive in non-labeled residues (i.e., a 1:1 substitution). Land preparation and corn seeding will follow, using identical methods as those used for the rest of the main experiment, and fertilizers will be analyzed for 15N. At harvest, we will collect whole corn plants and three additional soil cores per microplot and analyze them for 15N. All 15N samples will be analyzed by combustion, using an elemental analyzer coupled to a mass spectrometer. We will use an isotope mixing model with three pools (chickpea residue N, fertilizer N, soil N) to quantify the amount of N transferred from chickpea to the subsequent corn crop and to the soil.

At both PSREU and FAMU research stations, we will monitor N-cycling using traditional methods, focusing on the 6-8 varieties selected for objective 1 in addition to the rye cover crop (total: 28 to 36 plots per site per year). We will quantify soil extractable N using 2M KCl in the tilled layer (0-20 cm) before chickpea/rye planting, midway during the chickpea/rye growing season, after chickpea/rye termination (and before corn planting), midway in the corn growing season, and after corn harvest. We will collect soils for potential net N mineralization (a 28-day incubation) for all of these time steps, using the method of Roberston et al. (1999). After chickpea/rye termination, we will build N mineralization curves to determine the temporal release of N from chickpea/rye residues over time, measuring soil-extractable N at four time points during a two-month incubation.

We will also measure soil protein and permanganate-oxidizable C (POXC), according to Stott et al. (2019), before chickpea/rye planting, after chickpea/rye termination, and after corn harvest, to measure changes in emerging soil health indicators. Before corn planting, we will measure traditional soil fertility indicators (Mehlich-extractable micro- and macronutrients, soil pH) to adjust fertilization rates, using an external laboratory. Finally, at both research sites, we will collect crops for total N analysis (chickpea/rye aboveground biomass, corn aboveground biomass and seeds) in each plot in each year, and we will determine total N and C by combustion.

For on-farm trials, we will focus on measurements of crop N in chickpea and corn, incubations quantifying N release after chickpea termination, soil protein N and POXC (before chickpea, after chickpea, after corn), and traditional soil properties measured before corn. These indicators are pre-selected as they provide information that should be most applicable to growers, although we will refine the choice of indicators with the advisory council and participating growers.

All data collected for objective 2 will be analyzed using analysis of variance (ANOVA), using a different ANOVA for each research station (i.e., PSREU, FAMU), with chickpea varieties as a fixed factor and block as a random factor. When multiple measurements are taken from a given plot in a year (e.g., N mineralization), a repeated measures model will be used. For on-farm trials, all sites will be analyzed at once, using site as a fixed effect in the model. Tukey HSD tests will be used for means separation, and appropriate data transformations will be used prior to analysis to conform with conditions of normality of residuals and homogeneity of variances. All analyses will be conducted in R.

Co-PIs Maltais-Landry and Wilson will lead research activities laid out in objective 2.

Objective 3:
Monitoring provides information on pest population density and is the cornerstone of any pest management program. Chickpea is a leguminous annual plant that is attacked by a host of pests including, beet armyworm, Spodoptera exigua; chickpea leafminer, Liriomyza cicerina; cowpea aphid, Aphis craccivora; and pod borers, Helicoverpa armigera.

The corn earworm (CEW) Helicoverpa zea Boddie is a major pest of corn in the Southern Coaster Plain areas (Reay-Jones 2019). The larva feeds on several field and horticultural crops including alfalfa, clover, cotton, oat, millet, corn, and sorghum. In corn, the larva initially feeds on silk before moving to the developing kernels.

The European corn borer (ECB) is an important pest of field crops that cause an estimated $1 billion in losses annually (Hutchinson et al. 2010). ECB was introduced into the eastern US in 1917. The larva feeds on the silk eventually gaining access to the kernels. In the southern US there are three to four generations per year.

The southern corn rootworm (SCR), Diabrotica undecimpunctata howardi also known as the spotted cucumber beetle is common in southeastern US. A female can lay up to 500 eggs in its lifetime (Farms. Com). Depending on climate, the SCR can have up to 3 -4 generations per year. Both adults and larvae feed on a wide range of field crops but the larva is the more damaging life-stage. The larva feeds on the terminal blades making round holes and later in the season when the roots are established, they will begin feeding on the roots.

Methodology:
We will use several monitoring techniques to quantify the major pests in chickpea and corn that are common to North Florida. Insects and beneficials will be monitored in selected chickpea varieties to assess levels of susceptibility. Pheromone traps will be deployed to monitor the flight activity of adult beet armyworm and pod borers in Chickpea. The larvae of beet armyworm and pod borers will be monitored by shaking known number of plants and counting the number of larvae that fall onto a drop cloth held beneath the canopy. Aphids and leafminers will be monitored using unbaited yellow sticky cards and using in situ counts.

We will also monitor CEW, ECB, and SCR in corn/chickpea (research plot) and a grower standard corn/rye. We will compare the abundance of pests and beneficials in these two systems. The corn earworm will be sampled by randomly choosing known numbers of plants at each location. Each plant (seed heads) will be vigorously shaken over a beat sheet and the number of larvae that fall onto the sheet will be counted and recorded. For the ECB, we will initially deploy two baited pheromone traps (E race & Z race) of the Heliothis (Hartstack) style, which will be checked weekly. After the trap-catch is initiated, we will count egg masses and young larvae found on the plant. Sampling for ECB egg masses will involve examining the upper and lower sides of the corn ear leaf, on approximately 10 plants (one leaf per plant). We will also examine the leaf junctions for larvae and record the number of caterpillars found. Root assessment for larval feeding will be made at three random locations in each field. We will inspect 5 consecutive root balls to assess root injury. In addition to major pests of corn, we will also sample for beneficial insects such as parasitoids and predators. Egg parasitoids of CEW and ECB include Trichogramma spp., and Telenomus spp. whereas larval parasitoids include Cotesia spp., and Campoletis spp. Predators typically feed on eggs and larvae of corn earworm and ECB. Some common predators in the corn system that will be assessed include the lady bird beetle, Hippodamia convergens Guerin-Meneville, lacewings, Chrysopa and Chrysoperla spp., minute pirate bug, Orius spp. and big-eyed bugs, Geocoris spp..

Monitoring data will be compared according to varieties analyzed using repeated measures ANOVA. Pest and beneficial insect counts will be transformed to ln (x+0.5) to normalize the distribution and homogenize the variances among before analysis. Treatment means will be separated by Tukey’s HSD test. We will also t-tests to determine differences between our research plots and the grower standard. Co-PI Liburd will lead research activities and data analysis for objective 3.

Objective 4:
We will develop Partial Budgets to compare selected chickpea varieties' cost-effectiveness in Years 2 and 3. Partial Budget Analysis (PBA) is a commonly used technique to assess the impact of quantifiable economic changes in both costs and returns in a farm enterprise (Kay et al., 1994). PBA compares the negative effects (i.e., estimated cost) and positive effects (i.e., estimated returns) of employing a new treatment relative to the cost and returns of a baseline treatment. Total effects are calculated by subtracting the estimated negative impact from positive effects attributed to a new treatment. The use of PBA is appropriate when evaluating and comparing the impact of alternative production techniques where there is a single variant (in our case, the dual-use chickpea as cash and cover crop) in the production system (Wossink and, Osmond, 2002). We will use the PBA format suggested by Dalsted and Gutierrez (1992).

Our analysis will account for changes in the structure of production costs, including operational costs (e.g., labor, machinery, and material) associated preharvest, harvest, and production stages of chickpeas. Data for this analysis will come from observations collected in field trials, public sources, and surveys available through federal and state/regional agencies, and the academic literature. To validate the degree of accuracy of cost and revenue estimates drawn from literature and market surveys, we will convene a panel of 6 growers and use the Delphi Method—a process which aims to achieve convergence of opinion on a specific question or topic (Linstone and Turoff, 2002; Okoli and Pawlowski, 2004).The results of the economic analysis will provide side-by-side cost-effectiveness comparisons of selected chickpea verities. Co-PI Ruiz-Menjivar will lead research activities for objective 4.

Objective 5:
Active grower participation in the research process from conceptualization through implementation and outreach is critical to the success of this project. We use two specific activities to ensure that growers are aware of and informed about the project and that they play an active, decisive role in the development of the project.

The Advisory Council is a permanent governing body for the duration of the project that will meet bi-annually to assess overall results, discuss progress and impacts, and determine if the project plan requires adjustments. We will seek nominations from county and district Extension personnel and from individuals who have formal and informal leadership roles in their communities and who have collaborated previously with researchers and Extension from FAMU and UF. The AC will (1) provide targeted consensus-based input to refine and improve research activities and (2) detailed reviews of progress for each of the four research objectives. Dr. Swisher will facilitate the discussions to help ensure that the AC can reach consensus-based recommendations necessary to ensure scientific and methodological rigor, reduce research bias, and enhance research outcomes and the potential quality of findings. We will summarize the impact of these recommendations in the final project report.

The Field Research Assessments are conducted by small groups (maximum of 10 participants) who are convened ad hoc. We will conduct separate assessments for growers and for technical advisors. The participants first complete individual visual assessments of the treatments in the research setting. They know what treatments are used, but the plots are not labelled to prevent bias based on prior experience or knowledge. After the visual assessment, the groups learn what treatments they observed and also the research results to that time in the project. Extension and other personnel convene separately to make specific recommendations. We have used this technique successfully for the past five years to improve biological research outputs and identify critical factors that influence growers' assessments of alternative treatments. The output of these assessments is recommendations for ways to enhance the quality of our research, and these recommendations provide clear guidance about what aspects of our research are likely to be most "adoptable" by growers.

We will need Institutional Review Board (IRB) approval for the human subject research component of activities. We will use qualitative data analysis techniques to analyze the data, focusing on the themes and patterns of responses that are most important for project success. Our qualitative approach involves four steps that collapses original codes to a set of over-arching themes that capture the concepts that are shared by many, sometimes all, respondents. Reaching consensus is a challenging task for participants in both roles. Dr. Swisher has lengthy experience in facilitation, much of it with farmers and Extension agents, and she will lead the activities in objective 5.